Triple
T10504933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimbabwean general election, 2000 |
E247761
|
entity |
| Predicate | numberOfAppointedSeats |
P31811
|
FINISHED |
| Object | 30 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 30 | Statement: [Zimbabwean general election, 2000, numberOfAppointedSeats, 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAppointedSeats Context triple: [Zimbabwean general election, 2000, numberOfAppointedSeats, 30]
-
A.
numberOfAppointedMembers
chosen
Indicates the specific count of members who have been formally appointed to a group, body, or position.
-
B.
numberOfElectedMembers
Indicates the total count of individuals who have been formally chosen through an election to serve as members of a given body or group.
-
C.
governingBodySeats
Indicates the number of seats or positions an entity holds in a specified governing body.
-
D.
numberOfAtLargeSeats
Indicates the total count of at-large seats (positions not tied to specific districts or subunits) associated with an entity.
-
E.
numberOfSeatsWon
Indicates the quantity of seats secured by an entity (such as a party or candidate) in an election or representative body.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5099f4dec8190a9851739c8bc9a69 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:26 p.m.